Efficient global robustness certification of neural networks via interleaving twin-network encoding

Z Wang, C Huang, Q Zhu - 2022 Design, Automation & Test in …, 2022 - ieeexplore.ieee.org
The robustness of deep neural networks has received significant interest recently, especially
when being deployed in safety-critical systems, as it is important to analyze how sensitive …
被引用次数：20 相关文章

Efficient Global Robustness Certification of Neural Networks via Interleaving Twin-Network Encoding

Z Wang, C Huang, Q Zhu - 2022 Design, Automation and …, 2022 - scholars.northwestern.edu
The robustness of deep neural networks has received significant interest recently, especially
when being deployed in safety-critical systems, as it is important to analyze how sensitive …

Efficient Global Robustness Certification of Neural Networks via Interleaving Twin-Network Encoding

Z Wang, C Huang, Q Zhu - openreview.net
The robustness of deep neural networks has received significant interest recently, especially
when being deployed in safety-critical systems, as it is important to analyze how sensitive …

Efficient Global Robustness Certification of Neural Networks via Interleaving Twin-Network Encoding

Z Wang, C Huang, Q Zhu - arXiv e-prints, 2022 - ui.adsabs.harvard.edu
The robustness of deep neural networks has received significant interest recently, especially
when being deployed in safety-critical systems, as it is important to analyze how sensitive …

Efficient Global Robustness Certification of Neural Networks via Interleaving Twin-Network Encoding

Z Wang, C Huang, Q Zhu - arXiv preprint arXiv:2203.14141, 2022 - arxiv.org
The robustness of deep neural networks has received significant interest recently, especially
when being deployed in safety-critical systems, as it is important to analyze how sensitive …

Efficient global robustness certification of neural networks via interleaving twin-network encoding

Z Wang, C Huang, Q Zhu - Proceedings of the 2022 Conference & …, 2022 - dl.acm.org
The robustness of deep neural networks has received significant interest recently, especially
when being deployed in safety-critical systems, as it is important to analyze how sensitive …
[PDF] nsf.gov

[PDF][PDF] Efficient Global Robustness Certification of Neural Networks via Interleaving Twin-Network Encoding

Z Wang, C Huang, Q Zhu - 2022 Design, Automation & Test in Europe …, 2022 - par.nsf.gov
The robustness of deep neural networks has received significant interest recently, especially
when being deployed in safety-critical systems, as it is important to analyze how sensitive …
[PDF] ijcai.org

[PDF][PDF] Efficient Global Robustness Certification of Neural Networks via Interleaving Twin-Network Encoding

Z Wang, C Huang, Q Zhu - ijcai.org
The robustness of deep neural networks in safetycritical systems has received significant
interest recently, which measures how sensitive the model output is under input …

Efficient Global Robustness Certification of Neural Networks via Interleaving Twin-Network Encoding

Z Wang, C Huang, Q Zhu - 32nd International Joint …, 2023 - scholars.northwestern.edu
The robustness of deep neural networks in safety-critical systems has received significant
interest recently, which measures how sensitive the model output is under input …

Efficient global robustness certification of neural networks via interleaving twin-network encoding

Z Wang, C Huang, Q Zhu - … of the Thirty-Second International Joint …, 2023 - dl.acm.org
The robustness of deep neural networks in safetycritical systems has received significant
interest recently, which measures how sensitive the model output is under input …